5f6c9b8ca29b56ab2d2e1acfc38ea61001b92c4b,allennlp/common/testing/model_test_case.py,ModelTestCase,ensure_batch_predictions_are_consistent,#ModelTestCase#,147

Before Change

                        // elements in the batched case.  Fixing this in general is complicated;
                        // we"ll just fix some easy cases that we actually have, for now.
                        num_tokens = single_predicted.size(0)
                        if batch_predicted.dim() == 1:
                            batch_predicted = batch_predicted[:num_tokens]
                        elif batch_predicted.dim() == 2:
                            batch_predicted = batch_predicted[:num_tokens, :]
                        else:
                            raise NotImplementedError
                    assert_allclose(single_predicted.data.numpy(),
                                    batch_predicted.data.numpy(),
                                    atol=tolerance,
                                    err_msg=key)

After Change

                batch_predicted = batch_predictions[key][i]
                if isinstance(single_predicted, torch.autograd.Variable):
                    if single_predicted.size() != batch_predicted.size():
                        slices = tuple(slice(0, size) for size in single_predicted.size())
                        batch_predicted = batch_predicted[slices]
                    assert_allclose(single_predicted.data.numpy(),
                                    batch_predicted.data.numpy(),

Instances